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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Workflow Integration and Solution Design | 16% | - Use Claude for research, planning, and process optimization - Analyze requirements and use cases - Support solution design through iteration - Integrate Claude into existing workflows and communicate its value and limitations |
| Topic 2: Troubleshooting and Optimization | 10% | - Adjust approaches based on feedback and results - Optimize workflows for efficiency and effectiveness - Identify and diagnose issues with underperforming prompts or poor outputs |
| Topic 3: Configuration and Knowledge Management | 12% | - Create effective system-level instructions - Maintain and update configurations - Manage uploaded knowledge and connectors - Configure Claude Projects with instructions and knowledge sources |
| Topic 4: Prompting and Task Execution | 14% | - Adapt prompting strategy by task type - Apply task decomposition techniques to structure complex requests - Create effective prompts for business and technical tasks - Iterate prompts to improve output quality |
| Topic 5: Product and Model Selection | 12% | - Align model selection with task requirements - Select appropriate Claude product features - Differentiate between Claude model types - Manage context limitations and memory |
| Topic 6: Output Evaluation and Validation | 21% | - Determine when human review or additional verification is required - Edit and adapt outputs for the intended audience - Organize and curate information and select appropriate output formats - Apply fact-checking and validation techniques - Evaluate Claude-generated outputs for accuracy and completeness - Identify hallucinations, inconsistencies, and biases in responses |
| Topic 7: Governance, Risk, and Responsible Use | 15% | - Understand ethical implications of Claude use - Follow organizational AI policies and governance standards - Identify appropriate and inappropriate use cases - Apply data sensitivity, regulatory, and privacy considerations |
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NEW QUESTION # 67
A knowledge worker is iterating a prompt that has produced a partly acceptable response.
Which refinement practice produces the strongest learning across iterations?
Answer: A
Explanation:
Under the objective Iterate prompts to improve output quality , systematic prompt optimization relies on disciplined, hypothesis-driven iteration using controlled variables.
When a prompt yields a partially acceptable result, modifying a single isolated element at a time-such as refining role framing, adjusting format constraints, or adding specific negative constraints-allows the user to establish clear causality between the prompt modification and the resulting output change (Option A).
Documenting the effect of each adjustment ensures reproducible, predictable improvements. Conversely, making multiple simultaneous revisions (Options C and D) confounds the evaluation, making it impossible to determine which specific change helped or degraded output quality. Discarding work entirely on each run (Option B) eliminates incremental learning and increases iteration time.
NEW QUESTION # 68
You are reviewing a Claude-generated report whose tone is confident throughout.
Which question best separates plausibility from verification?
Answer: C
Explanation:
Option A is correct because confident language, logical flow, and professional formatting do not establish factual accuracy. Verification requires checking whether each material claim is supported by a credible external source or by the authoritative input supplied for the task. Claims that cannot be traced should be removed, qualified as uncertain, or subjected to additional research.
Anthropic warns that even advanced Claude models can generate information that is factually incorrect or inconsistent with the provided context. Its recommended safeguards include allowing Claude to acknowledge uncertainty, grounding factual work in direct quotations, requiring citations, and checking whether supporting evidence actually establishes each claim. A citation must also be evaluated for relevance and credibility; merely attaching a source does not prove that the source supports the precise statement.
Options B, C, and D assess presentation characteristics rather than verification. Length and section count do not prove completeness, a strong opening does not validate the conclusion, and varied sentence structure concerns writing style. A plausible response can satisfy all three while containing unsupported assertions.
Consequently, claim-level traceability is the decisive test separating an answer that merely sounds credible from one that has been verified. See Anthropic's hallucination-reduction and citation guidance .
NEW QUESTION # 69
You are a compliance specialist applying the organization's policy to a proposed Claude use case.
Which policy-application step should be performed first?
Answer: B
Explanation:
Answer A is correct. Policy application must begin by identifying the provisions that govern the proposed Claude use case. The specialist first needs to understand the use case's purpose, users, data, affected individuals, intended outputs, level of automation, and potential consequences. These characteristics determine which organizational requirements concerning privacy, security, human oversight, acceptable use, regulated activities, and recordkeeping are applicable.
After identifying the relevant provisions, the specialist compares the proposed use case against those requirements, corresponding to Option D. Based on that assessment, the specialist can approve the use case, require modifications or safeguards, or reject it, as described in Option B. The use case, analysis, controls, and final decision should then be recorded in the compliance register, corresponding to Option C. The logical sequence is therefore A, D, B, and C.
Starting with approval would be premature because no compliance analysis has occurred. Similarly, a meaningful comparison cannot be completed until the applicable provisions have been identified.
Documentation is important, but it records the assessment and decision rather than replacing them. Correct policy application therefore begins with scope determination and proceeds through comparison, decision, and documentation. This supports consistent governance and an auditable decision trail. Anthropic Usage Policy
NEW QUESTION # 70
You are a Claude associate assessing a proposed Claude use case before approving it for your team.
Which is the correct order of assessment steps?
(1) Compare the use case against the organization's policies and the relevant regulatory considerations.
(2) Document the assessment outcome and the rationale for traceability.
(3) Identify the audience, decision impact, and reversibility of the outputs.
(4) Decide whether the use case proceeds, requires modification, or is declined.
(5) Identify the data types involved and whether sensitive data is implicated.
Answer: D
Explanation:
A sound assessment begins by establishing who will receive or rely on the output, the consequences of an incorrect result, and whether the resulting action can be reversed. This initial impact analysis determines the level of scrutiny required. The assessor should then identify the data involved, especially personal, confidential, regulated, or otherwise sensitive information. Once the use case and its information exposure are understood, it can be compared meaningfully against organizational AI policies, legal requirements, and regulatory restrictions.
The next step is to decide whether the use case should proceed, be modified with safeguards, or be rejected.
Documentation comes last because it records the completed assessment, decision, supporting evidence, restrictions, and rationale for auditability. Therefore, the correct order is 3,5,1,4,2.
This sequencing reflects the AI Fluency principles of Delegation and Diligence: humans determine whether and how AI should be used and remain responsible for the consequences. Anthropic also advises users to be thoughtful about highly sensitive personal and business information. Options A, C, and D place policy review or data classification before the use case's audience and impact have been properly established. Anthropic AI Fluency
NEW QUESTION # 71
You are an operations lead sorting proposed Claude use cases according to whether they are acceptable for your team to pursue.
Which two proposed use cases are acceptable for the team to pursue with Claude? (Select two.) Each correct answer presents a complete solution.
Answer: C,E
Explanation:
Answers B and C are the two acceptable use cases as written. Drafting an internal training summary from approved documentation is a bounded synthesis task grounded in authorized sources. Synthesizing themes from approved customer feedback under established aggregation rules is likewise a controlled analysis task, provided the data handling follows organizational privacy requirements. Both activities support human work without assigning Claude a consequential decision about an individual. Option D feeds performance-review information into a promotion process, an employment-related high-risk domain requiring formal controls and accountable human judgment. Options A and E involve healthcare and legal work. Anthropic's current Usage Policy does not categorically ban those domains, but it requires qualified professional review for high-risk advice or decisions and requires disclosure when outputs are presented directly to consumers. The brief wording in A and E mentions professional review but does not establish the complete safeguards, authorization, privacy handling, or disclosure needed to treat the workflow as approved. Therefore, they are not unconditionally acceptable "as stated." Anthropic's AI Fluency Delegation principle also requires considering consequences, reversibility, and the human capabilities that must remain in the process. B and C are the only choices that fully specify low-risk, policy-bounded knowledge work without relying on unstated safeguards. Anthropic Usage Policy
NEW QUESTION # 72
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